APPLICATION OF LINEAR AND NONLINEAR EXTRAPOLATIONS IN ANALYZING THE TRENDS OF CHANGES IN FINANCIAL STABILITY

• Main Author: EVGENY Negashev
• Format: Article
• Language: Russian
• Published: Government of Russian Federation, Financial University 2019-01-01
• Series: Учёт. Анализ. Аудит
• Subjects: линейная экстраполяция; нелинейная экстраполяция; критериальная функция финансовой устойчивости; показатель обеспеченности запасов общей величиной основных источников формирования; движение к кризисному финансовому состоянию; скорость изменения показателя финансовой устойчивости; ускорение изменения показателя финансовой устойчивости; кинематическая модель равноускоренного изме- нения показателя; погрешности аппроксимирующей функции при ретроспективных расчетах; linear extrapolation; non-linear extrapolation; criterion function of financial stability; ratio of stocks to a total value of the major sources of formation; movement to the crisis financial condition; rate of change of the financial stability indicator; accelerated rate of change of the financial stability indicator; kinematic model of uniformly accelerated change of the indicator; errors when using an approximating function in retrospective calculations
• Online Access: https://accounting.fa.ru/jour/article/view/84

The article researches the possibilities of applying the methods of linear and nonlinear extrapolation in the predictive analysis of a company’s financial stability based on the study of its trends. Analytical balance modelscan be used to detect and measure the trends of the changes in the financial state of a company. The indicators of trends intensity and the projected time to approach the border of the crisis financial condition built using the analytical balance model which are calculated on the basis of accounting and reporting data, allow commercial organizations to detect and quantify the negative trends when conducting the financial analysis. The author develops several algorithms to evaluating the trends of decrease of commercial organization’s financial stability. The article offers several algorithms based on application of linear and non-linear extrapolation of financial indicators depending on the amount of the information used for analysis.The practical significance of the proposed algorithms is related to their applicability to estimate the period of time during which the action of negative trends may lead to the crisis in the financial position of a company. This time period is an essential parameter for developing a financial recovery plan.